docs: def has_no_fat_ends(neuron, multiple_of_mean=2.0, final_point_count=5):
      '''Check if leaf points are too large
  
      Arguments:
          neuron(Neuron): The neuron object to test
          multiple_of_mean(float): how many times larger the final radius
          has to be compared to the mean of the final points
          final_point_count(int): how many points to include in the mean
  
      Returns:
          CheckResult with result list of ids of bad sections
  
      Note:
          A fat end is defined as a leaf segment whose last point is larger
          by a factor of `multiple_of_mean` than the mean of the points in
          `final_point_count`
      '''
      bad_ids = []
      for leaf in _nf.iter_sections(neuron.neurites, iterator_type=Tree.ileaf):
          mean_radius = np.mean(leaf.points[1:][-final_point_count:, COLS.R])
  
          if mean_radius * multiple_of_mean <= leaf.points[-1, COLS.R]:
              bad_ids.append((leaf.id, leaf.points[-1:]))
  
      return CheckResult(len(bad_ids) == 0, bad_ids)